文献类型：期刊文献

中文题名：基于增强Frost局部滤波及单木距离图重构标记的CHM树冠分割

英文题名：Crown segmentation of CHM based on the enhanced frost local filtering and distance map reconstruction

作者：张华聪[1,2,3] 谭新建[3] 喻龙华[3] 厉月桥[3] 陈永富[1,2] 刘仁[3] 张怀清[1,2]

第一作者：张华聪

机构：[1]中国林业科学研究院资源信息研究所,北京100091;[2]国家林业和草原局林业遥感与信息技术重点实验室,北京100091;[3]中国林业科学研究院亚热带林业实验中心,江西新余336600

年份：2023

卷号：47

期号：5

起止页码：9-18

中文期刊名：南京林业大学学报:自然科学版

外文期刊名：Journal of Nanjing Forestry University:Natural Sciences Edition

收录：CSTPCD;;Scopus;北大核心:【北大核心2020】；CSCD:【CSCD2023_2024】；

基金：中国林业科学研究院资源信息研究所基本科研业务费专项(CAFYBB2019SZ004,CAFYBB2021ZE005)。

语种：中文

中文关键词：无人机激光点云;林冠高度模型(CHM);增强Frost滤波;距离图重构标记;树冠分割

外文关键词：UAV laser point cloud;cannopy height model(CHM);enhance Frost;distance map marker and reconstruction;crown segmentation

分类号：S758.5

摘要：【目的】利用增强Frost局部滤波和单木距离图重构标记技术对冠层高度模型(CHM)进行分割,以提高无人机激光雷达在单木树冠分割的精度和效率。【方法】选取江西分宜山下实验林场阔叶混交林、针叶混交林和针阔混交林3个不同类型的林分为研究对象,以无人机激光雷达数据为数据源,构建CHM。针对高分辨率CHM树冠区域孔隙较多的问题,利用增强Frost局部滤波处理优化CHM,优化结果与不同滤波方法进行了比较分析;然后应用距离图重构标记分割技术对增强Frost局部滤波优化后的0.1、0.2、0.5及1.0m分辨率的CHM进行分割与分析;最后确定最佳分辨率的CHM,并其将分割结果与同等分辨率下分水岭算法以及点云分割均值偏移算法结果进行比较。【结果】采用增强Frost局部滤波处理的CHM优化效果显著,在有效抑制树冠噪音的同时,也能较好地保留图像细节信息。0.2m分辨率的CHM分割效果最佳。距离图重构标记分割方法分割针叶混交林、针阔混交林、阔叶混交林3种不同林分类型的分割精度(0A)分别为0.96、0.84、0.75;根据树冠分割结果计算单木冠幅,冠幅估测的决定系数R分别为0.83、0.82、0.71。【结论】基于增强Frost局部滤波及距离图重构标记技术可实现对激光点云CHM的单木分割和树冠估算,能够满足森林调查和监测的基本需求。
【Objective】We used the enhanced Frost local filtering and single-tree distance map reconstruction marking technology to segment a canopy height model(CHM),improving the accuracy and efficiency of unpiloted aerial system(UAV)-light detection and ranging(LiDAR)segmentation in single-tree crowns.【Method】We selected three forest types-coniferous mixed,coniferous-broad mixed,and broad-leaved mixed-in the Shanxia Experimental Forest Farm of Fenyi,Jiangxi Province.We then used UAV-LiDAR data to construct the CHM.To combat the increased pores in the crown area of the high-resolution CHM,we used the enhanced Frost local filtering to optimize the CHM and results were compared with different filtering methods.Next we applied the distance map reconstruction marker segmentation technology to segment and analyze the CHM-with resolutions of 0.1,0.2,0.5 and 1.0 m after optimization of the enhanced Froest local filter.Finally,we determined the CHM with the optimal resolution,and compared segmentation results with that of a watershed algorithm with the same resolution and mean-shift segmentation algorithm.【Result】Applying the enhanced Frost local filter indeed optimized the CHM-preserving image details while suppressing phase crown noise.A resolution of 0.2 m performed best for the CHM segmentation.An overall accuracy of 0.96,0.84 and 0.75 was observed for coniferous mixed,coniferous-broad mixed,and broad-leaved mixed forests,respectively.The crown width of a single tree was calculated according to crown segmentation results,and the R^(2) estimated at 0.83,0.82 and O.71,respectively.【Conclusion】Through the enhanced Frost local filtering and distance map reconstruction marking technology,the single-tree segmentation and crown estimation of laser point cloud CHMs can be realized,meeting key requirements of forest surveys and monitoring.